The Trump administration’s hostility toward data collection is not incidental—it is ideological.
By Matthew A. McIntosh
Public Historian
Brewminate
Introduction
In the digital age, data is more than numbers and spreadsheets—it’s the bedrock of public policy, social equity, and scientific advancement. Federal data collection is a critical mechanism through which governments understand the needs of their people, measure progress, and respond to crises. Under the administration of Donald J. Trump, however, these systems have faced significant erosion. From population counts to environmental monitoring, federal data collection has not only been deprioritized but actively undermined. It is worth examining how his actions have affected America’s statistical infrastructure—and what a second term will mean.
The Assault on Objectivity
The Trump administration’s hostility toward data collection is not incidental—it is ideological. A central theme of Trump’s presidency is the rejection of what his supporters derided as the “deep state” and “elitist expertise.” That mindset manifests in repeated clashes with federal agencies responsible for gathering data that might contradict the administration’s political messaging.
Take, for instance, the U.S. Census Bureau. In 2018, the Trump administration attempted to add a citizenship question to the 2020 Census, arguing that it was necessary to enforce the Voting Rights Act. In reality, internal memos and court testimony later revealed that the real goal was to depress response rates among immigrant communities, thus skewing congressional representation and federal funding allocations toward whiter, more Republican areas. The Supreme Court blocked the question, but the damage was already done: fear and confusion among marginalized communities led to undercounts, which will affect redistricting and resource distribution for a decade.
Similarly, the Environmental Protection Agency (EPA) saw a rollback in data transparency and scientific rigor. In 2020, the Trump EPA finalized a rule dubbed the “Strengthening Transparency in Regulatory Science” rule, which effectively excluded scientific studies that did not make all underlying data publicly available—an often impossible demand when research involves confidential medical data. Critics rightly saw this as a way to sideline major public health research linking pollution to disease, thereby weakening environmental regulations under the guise of transparency.
Silencing Science and Surveillance
The war on data extends deeply into the scientific realm. The Trump administration repeatedly muzzles scientists and distorts or suppresses data that contradicts its political agenda. The White House Coronavirus Task Force, for example, was accused of manipulating COVID-19 data and sidelining the Centers for Disease Control and Prevention (CDC) at critical junctures of the pandemic.
In 2020, the Department of Health and Human Services (HHS) ordered hospitals to send COVID-19 patient data to a private contractor-run system instead of the CDC’s established platform. The new system, hastily rolled out and plagued by technical issues, lacked transparency and created delays in pandemic response. The sidelining of the CDC was emblematic of a broader distrust of long-standing public health infrastructure.
In another striking example, the National Oceanic and Atmospheric Administration (NOAA) was dragged into political controversy when Trump insisted, incorrectly, that Hurricane Dorian would strike Alabama. When meteorologists at the Birmingham office of the National Weather Service contradicted him, NOAA leadership issued an unusual statement rebuking their own scientists—a move widely criticized as political interference in scientific communication.
Gutting Federal Expertise
One of the most effective ways to cripple data collection is to destroy the institutions responsible for it. The Trump administration does just that, most dramatically with the U.S. Department of Agriculture (USDA). In 2019, the USDA relocated two major research divisions—the Economic Research Service (ERS) and the National Institute of Food and Agriculture (NIFA)—from Washington, D.C., to Kansas City, Missouri. While framed as a cost-saving measure, the result was a mass exodus of experienced economists and scientists who chose not to relocate. Over 75% of staff either quit or were let go. The brain drain devastated research capacity on topics like food insecurity, climate change, and rural development.
Likewise, the Office of Personnel Management (OPM), the agency that handles federal hiring, saw plans for restructuring that alarmed experts concerned about preserving a professional civil service insulated from political pressure. The Trump administration’s push to reclassify civil servants into a new “Schedule F” designation would have stripped protections from tens of thousands of federal workers, making it easier to fire them for political reasons. Though the order was rescinded by President Biden, Trump has signaled he would reinstate it if re-elected.
The Legacy of Data Destruction
The cumulative effect of these actions is more than the sum of their parts. Federal data collection is a slow-moving, methodical process—once disrupted, it can take years to rebuild. Missing or corrupted data can have cascading effects: misallocated funds, skewed research, flawed legislation, and poor crisis response. For example, inaccurate census data will affect federal funding distribution for over 130 programs, including Medicaid, school lunches, and public housing, until the 2030 count. Similarly, undermining climate research delays mitigation efforts just as global temperatures reach critical thresholds.
Furthermore, the erosion of public trust in federal data has long-term consequences. If Americans believe that data is politicized or unreliable, they may be less likely to participate in surveys, comply with public health recommendations, or trust government institutions.
What a Second Trump Term Could Bring
Trump has made no secret of his plans to intensify his dismantling of the administrative state. Project 2025—a policy blueprint crafted by conservative think tanks aligned with Trump—lays out a roadmap for centralizing power in the executive branch and curbing the influence of independent agencies. This includes further defunding and restructuring of federal statistical agencies, curbing regulatory powers, and purging career civil servants.
Given the historical context, it’s likely that a second Trump term will target agencies like the Census Bureau, CDC, EPA, and ERS with even more aggressive budget cuts, personnel purges, and policy constraints. The goal is not simply to reduce government inefficiency—it’s to ensure that the federal government cannot produce inconvenient truths.
Why It Matters
A functioning democracy depends on facts. Without reliable data, policymakers cannot make informed decisions, researchers cannot track trends, and journalists cannot hold the powerful accountable. Stripping away the government’s capacity to collect and analyze data isn’t just bureaucratic tinkering—it’s an assault on the public’s right to know.
The Trump administration’s legacy on federal data collection should serve as a warning. The deliberate weakening of federal data systems is not a victimless act. It affects every American—especially the most vulnerable—and threatens the integrity of governance itself. As voters consider the future of the country in the 2024 election and beyond, they must reckon with a sobering truth: democracy depends not just on votes, but on verifiable facts. Undermining data is undermining democracy.
Originally published by Brewminate, 05.14.2025, under the terms of a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license.
